SUMMARY The Molecular Interaction Center for Functional Genomics (MicFG) of Emory University proposes to understand the functions of genomic mutations in cancer etiology through systematic interrogation of mutant allele-mediated oncogenic protein-protein interactions (PPI) for target identification, validation, and perturbagen discovery across cancer types, as a contributing member of the CTD2 Network. For synergistic effort, we have a team of investigators and collaborators with complementary expertise in oncology, high throughput cancer biology and chemical biology, cancer genomics, bioinformatics, computational structural biology and cancer validation models. The wealth of available data for patient tumor-derived mutations offers unprecedented opportunities for translational research to develop personalized therapies. It is these genomic alterations in each driver gene that differentiate tumors from their normal counterparts. However, understanding how to leverage these genomic changes at the mutated amino acid resolution for cancer target discovery and how to rapidly translate this knowledge into genotype-directed cancer therapies for precision oncology remains a daunting and urgent challenge. Our proposal aims to address this critical bottleneck with a team effort by directly focusing on cancer mutation-created protein-protein interactions (neoPPI) for therapeutic discovery. To support this approach, we have generated a comprehensive database representing the landscape of major somatic missense mutations in TCGA pan-cancer datasets, and established a unique bioluminescence resonance energy transfer-based quantitative high throughput wildtype/mutant differential screening (qHT-dS) platform. We hypothesize that oncogenic neoPPIs can be rapidly uncovered by leveraging the cancer missense mutational landscape and implementing a combined high throughput informatics and differential PPI screening platform for discovery and validation of cancer targets for therapeutic discovery. To test this hypothesis, three specific aims are proposed: (i) to identify and validate cancer mutation-created neoPPIs through differential screening with the qHT-dS platform, (ii) to identify neoPPI disruptors as pathway perturbagens, and (iii) to develop and systematically apply integrated informatics pipelines for neoPPI discovery. Our studies will lead to (i) creation of cancer mutation expression vector libraries, large-scale PPI datasets, HTS neoPPI assays as a community resource, and discovery of (ii) tumor-specific neoPPIs as promising cancer-specific targets, (iii) selected neo-PPI perturbagens for oncogenic pathway disruption, and (iv) neoPPI informed potential biomarkers. Complementing the functional annotation of mutant alleles in in vivo models by others, our systematic identification of cancer gene variant- mediated neo-PPIs may reveal promising cancer-specific targets for genotype-directed therapeutic discovery.